Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
Department of Computer Science, UiT The Arctic University of Norway, Tromsø, Norway.
JMIR Public Health Surveill. 2021 Apr 23;7(4):e23806. doi: 10.2196/23806.
Consumer-based physical activity trackers have increased in popularity. The widespread use of these devices and the long-term nature of the recorded data provides a valuable source of physical activity data for epidemiological research. The challenges include the large heterogeneity between activity tracker models in terms of available data types, the accuracy of recorded data, and how this data can be shared between different providers and third-party systems.
The aim of this study is to develop a system to record data on physical activity from different providers of consumer-based activity trackers and to examine its usability as a tool for physical activity monitoring in epidemiological research. The longitudinal nature of the data and the concurrent pandemic outbreak allowed us to show how the system can be used for surveillance of physical activity levels before, during, and after a COVID-19 lockdown.
We developed a system (mSpider) for automatic recording of data on physical activity from participants wearing activity trackers from Apple, Fitbit, Garmin, Oura, Polar, Samsung, and Withings, as well as trackers storing data in Google Fit and Apple Health. To test the system throughout development, we recruited 35 volunteers to wear a provided activity tracker from early 2019 and onward. In addition, we recruited 113 participants with privately owned activity trackers worn before, during, and after the COVID-19 lockdown in Norway. We examined monthly changes in the number of steps, minutes of moderate-to-vigorous physical activity, and activity energy expenditure between 2019 and 2020 using bar plots and two-sided paired sample t tests and Wilcoxon signed-rank tests.
Compared to March 2019, there was a significant reduction in mean step count and mean activity energy expenditure during the March 2020 lockdown period. The reduction in steps and activity energy expenditure was temporary, and the following monthly comparisons showed no significant change between 2019 and 2020. A small significant increase in moderate-to-vigorous physical activity was observed for several monthly comparisons after the lockdown period and when comparing March-December 2019 with March-December 2020.
mSpider is a working prototype currently able to record physical activity data from providers of consumer-based activity trackers. The system was successfully used to examine changes in physical activity levels during the COVID-19 period.
基于消费者的身体活动追踪器日益普及。这些设备的广泛使用以及记录数据的长期性为流行病学研究提供了有价值的身体活动数据来源。挑战包括活动追踪器模型在可用数据类型、记录数据的准确性以及不同提供者和第三方系统之间如何共享数据方面存在很大的异质性。
本研究旨在开发一种系统，用于记录来自不同消费者身体活动追踪器提供者的身体活动数据，并研究其作为流行病学研究中身体活动监测工具的可用性。数据的纵向性质和同期的大流行爆发使我们能够展示该系统如何在 COVID-19 封锁前后用于监测身体活动水平。
我们开发了一种系统（mSpider），用于自动记录来自佩戴 Apple、Fitbit、Garmin、Oura、Polar、Samsung 和 Withings 等活动追踪器以及将数据存储在 Google Fit 和 Apple Health 中的追踪器的参与者的身体活动数据。为了在整个开发过程中测试系统，我们招募了 35 名志愿者，从 2019 年初开始佩戴提供的活动追踪器。此外，我们招募了 113 名在挪威 COVID-19 封锁期间佩戴私人活动追踪器的参与者。我们使用条形图和双侧配对样本 t 检验和 Wilcoxon 符号秩检验，检查了 2019 年至 2020 年期间每月的步数、中等至剧烈身体活动分钟数和活动能量消耗的变化。
与 2019 年 3 月相比，2020 年 3 月封锁期间，平均步数和平均活动能量消耗显著减少。步数和活动能量消耗的减少是暂时的，以下每月比较显示 2019 年和 2020 年之间没有显著变化。封锁期后和比较 2019 年 3 月至 12 月与 2020 年 3 月至 12 月时，观察到几个月的比较中中等至剧烈身体活动有少量显著增加。
mSpider 是一个工作原型，目前能够记录来自消费者身体活动追踪器提供者的身体活动数据。该系统成功用于检查 COVID-19 期间身体活动水平的变化。
